37 citations · 74 across the 8 of their papers we have counts for
8 papers
Remote Entanglement in Lattice Surgery: To Distill, or Not to Distill
Sitong Liu, John Stack, Ke Sun +5
Distributed quantum computing can potentially address the scalability challenge by networking processors through photon-mediated remote entanglement. Prior approaches assumed that…
The Practicality of Randomized Quantum Linear Systems Solvers
Siddharth Hariprakash, Roel Van Beeumen, Katherine Klymko +1
Randomized quantum algorithms have been proposed for quantum linear algebra with the goal of constructing shallower circuits than methods based on block encodings, and have been sp…
The Role of Quantum Computing in Advancing Scientific High-Performance Computing: A perspective from the ADAC Institute
Gilles Buchs, Thomas Beck, Ryan Bennink +19
Quantum computing (QC) has gained significant attention over the past two decades due to its potential for speeding up classically demanding tasks. This transition from an academic…
EHands: Quantum Protocol for Polynomial Computation on Real-Valued Encoded States
Jan Balewski, C. Pestano, Mercy G. Amankwah +3
We present EHands, a quantum-native protocol for implementing multivariable polynomial transformations on quantum processors. The protocol introduces four fundamental, reversible o…
Efficient Measurement-Driven Eigenenergy Estimation with Classical Shadows
Yizhi Shen, Alex Buzali, Hong-Ye Hu +4
Quantum algorithms exploiting real-time evolution under a target Hamiltonian have demonstrated remarkable efficiency in extracting key spectral information. However, the broader po…
Quantum Fourier Transform Revisited
Daan Camps, Roel Van Beeumen, Chao Yang
The fast Fourier transform (FFT) is one of the most successful numerical algorithms of the 20th century and has found numerous applications in many branches of computational scienc…
A greedy algorithm for computing eigenvalues of a symmetric matrix
Taylor M. Hernandez, Roel Van Beeumen, Mark A. Caprio +1
We present a greedy algorithm for computing selected eigenpairs of a large sparse matrix that can exploit localization features of the eigenvector. When the eigenvector to be c…
Approximate Green's Function Coupled Cluster Method Employing Effective Dimension Reduction
Bo Peng, Roel Van Beeumen, David B. Williams-Young +2
The Green's function coupled cluster (GFCC) method is a powerful many-body tool for computing the electronic structure of molecular and periodic systems, especially when electrons…